fix(agent): preserve interrupted tool-call turns
Keep tool-call assistant messages valid across provider sanitization and avoid trailing user-only history after model errors. This prevents follow-up requests from sending broken tool chains back to the gateway.
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@@ -84,6 +84,34 @@ class TestEnforceRoleAlternation:
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tool_msgs = [m for m in result if m["role"] == "tool"]
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assert len(tool_msgs) == 2
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def test_consecutive_assistant_keeps_later_tool_call_message(self):
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msgs = [
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{"role": "user", "content": "Hi"},
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{"role": "assistant", "content": "Previous reply"},
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{"role": "assistant", "content": None, "tool_calls": [{"id": "1"}]},
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{"role": "tool", "content": "result1", "tool_call_id": "1"},
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{"role": "user", "content": "Next"},
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]
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result = LLMProvider._enforce_role_alternation(msgs)
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assert result[1]["role"] == "assistant"
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assert result[1]["tool_calls"] == [{"id": "1"}]
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assert result[1]["content"] is None
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assert result[2]["role"] == "tool"
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def test_consecutive_assistant_does_not_overwrite_existing_tool_call_message(self):
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msgs = [
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{"role": "user", "content": "Hi"},
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{"role": "assistant", "content": None, "tool_calls": [{"id": "1"}]},
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{"role": "assistant", "content": "Later plain assistant"},
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{"role": "tool", "content": "result1", "tool_call_id": "1"},
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{"role": "user", "content": "Next"},
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]
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result = LLMProvider._enforce_role_alternation(msgs)
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assert result[1]["role"] == "assistant"
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assert result[1]["tool_calls"] == [{"id": "1"}]
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assert result[1]["content"] is None
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assert result[2]["role"] == "tool"
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def test_non_string_content_uses_latest(self):
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msgs = [
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{"role": "user", "content": [{"type": "text", "text": "A"}]},
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@@ -550,11 +550,40 @@ def test_openai_compat_preserves_message_level_reasoning_fields() -> None:
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{"role": "user", "content": "thanks"},
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])
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assert sanitized[1]["content"] is None
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assert sanitized[1]["reasoning_content"] == "hidden"
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assert sanitized[1]["extra_content"] == {"debug": True}
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assert sanitized[1]["tool_calls"][0]["extra_content"] == {"google": {"thought_signature": "sig"}}
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def test_openai_compat_keeps_tool_calls_after_consecutive_assistant_messages() -> None:
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with patch("nanobot.providers.openai_compat_provider.AsyncOpenAI"):
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provider = OpenAICompatProvider()
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sanitized = provider._sanitize_messages([
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{"role": "user", "content": "不错"},
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{"role": "assistant", "content": "对,破 4 万指日可待"},
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{
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"role": "assistant",
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"content": "<think>我再查一下</think>",
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"tool_calls": [
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{
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"id": "call_function_akxp3wqzn7ph_1",
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"type": "function",
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"function": {"name": "exec", "arguments": "{}"},
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}
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],
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},
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{"role": "tool", "tool_call_id": "call_function_akxp3wqzn7ph_1", "name": "exec", "content": "ok"},
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{"role": "user", "content": "多少star了呢"},
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])
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assert sanitized[1]["role"] == "assistant"
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assert sanitized[1]["content"] is None
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assert sanitized[1]["tool_calls"][0]["id"] == "3ec83c30d"
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assert sanitized[2]["tool_call_id"] == "3ec83c30d"
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@pytest.mark.asyncio
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async def test_openai_compat_stream_watchdog_returns_error_on_stall(monkeypatch) -> None:
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monkeypatch.setenv("NANOBOT_STREAM_IDLE_TIMEOUT_S", "0")
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